Radar devices are often used as driving support devices for motor vehicles. FM-CW (Frequency-Modulated Continuous Wave) radar devices are well known as such radar devices.
Typical FM-CW radar devices transmit, as a transmitted signal, a continuous radar wave, which is frequency modulated to have a frequency that increases in an up section over time and decreases in a down section over time; the up and down sections constitute one modulation cycle. The FM-CW radar devices receive, as received signals, arrival echoes (arrival waves) by respective receiving channels of a receiving antenna; the receiving channels are aligned in a row. The echoes are generated by reflection of the radar wave from a target, such as a point of an object that has reflected the radar wave.
The FM-CW radar devices generate, based on the received signals, information associated with the target that has reflected the radar wave. For example, such a typical FM-CW radar device is disclosed in Japanese Patent Application Publication No. 2006-47282.
Specifically, an FM-CW radar device of this type mixes the transmit signal with received signals (received echoes) to generate beat signals. Each of the beat signals has a frequency identical to a difference in frequency between a received signal by a corresponding receiving channel and the transmit signal. The FM-CW radar device performs spectrum analysis of each of the beat signals in each of the up and down sections to obtain peak frequency-components in intensity in each of the up and down sections. Each of the peak frequency-components means that there is a target candidate as the source of a corresponding arrival echo; the peak frequency-components will be referred to as “frequency peaks”.
Next, the FM-CW radar device performs one of known azimuth estimation algorithms, in other words, DOA (direction-of-arrival) estimation algorithms, to estimate the azimuth (direction) of an arrival echo, that is, an angle of an arrival echo from a corresponding target candidate with respect to a predetermined reference axis for each frequency peak. Then, the FM-CW radar device estimates the received power of the corresponding echo from the target candidate for each frequency peak.
Thereafter, the FM-CW radar device performs a known “pair-matching” task to extract, from the frequency peaks, at least one pair of a frequency peak in the up section and a corresponding frequency peak in the down section; the frequency peaks of the at least one pair meet both of the following conditions:
The first condition is that the difference in direction between an arrival echo corresponding to one of the frequency peaks of the at least one pair and an arrival echo corresponding to the other is within a predetermined angular range. The second condition is that the difference in received-power between the arrival echo corresponding to one of the frequency peaks of the at least one pair and the arrival echo corresponding to the other is within a predetermined power range.
The FM-CW radar device estimates that the extracted at least one pair of frequency peaks corresponds to at least one same target candidate that has reflected the radar wave.
Thus, the FM-CW radar device calculates the distance and the relative speed between the radar device and the corresponding at least one target candidate based on the at least one extracted pair of frequency peaks. Thus, the FM-CW radar device generates target information including the distance and the relative speed between the radar device and the corresponding at least one target candidate, and the azimuth of the corresponding at least one target candidate.
High resolution algorithms as the azimuth estimation algorithms are known. One of these high resolution algorithms is the MUSIC (Multiple Signal Classification) algorithm, and another is the ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm.
These high resolution algorithms generate an autocorrelation matrix of the received signals from the respective channels, obtain eigenvalues of the autocorrelation matrix, and estimate the number of arrival echoes based on the eigenvalues of the autocorrelation matrix. Particularly, the MUSIC algorithm obtains a MUSIC spectrum based on the number of arrival echoes and the eigenvalues, and extracts sharp peaks (deep nulls) in the MUSIC spectrum. Then, the MUSIC algorithm estimates the azimuth of a corresponding arrival echo for each extracted sharp peak, and estimates the received power of an arrival echo from the target for each extracted sharp peak.